Triple

T28106570
Position Surface form Disambiguated ID Type / Status
Subject People's Park (Shanghai) E710379 entity
Predicate contains P35 FINISHED
Object Shanghai Marriage Market
The Shanghai Marriage Market is a famous weekly gathering in Shanghai’s People’s Park where parents and matchmakers publicly advertise and negotiate potential spouses for unmarried adults, often via handwritten “marriage résumés.”
 E1801604 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Shanghai Marriage Market | Statement: [People's Park (Shanghai), contains, Shanghai Marriage Market]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Shanghai Marriage Market
Triple: [People's Park (Shanghai), contains, Shanghai Marriage Market]
Generated description
The Shanghai Marriage Market is a famous weekly gathering in Shanghai’s People’s Park where parents and matchmakers publicly advertise and negotiate potential spouses for unmarried adults, often via handwritten “marriage résumés.”

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ef9b71fdb081908b4a61cd7ff147c1 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f640c50dc88190a93952b9b87eb588 completed May 2, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15c92aeac8819082627315b96bccd6 completed May 26, 2026, 4:24 p.m.
NEDg Description generation batch_6a15c9d233048190a27d170dbe16c07e completed May 26, 2026, 4:26 p.m.
NED2 Entity disambiguation (via description) batch_6a15ca83e4588190baed86972447f0f8 completed May 26, 2026, 4:29 p.m.
Created at: April 27, 2026, 9:08 p.m.